2,056 research outputs found
Efficiency of prompt quarantine measures on a susceptible-infected-removed model in networks
This study focuses on investigating the manner in which a prompt quarantine
measure suppresses epidemics in networks. A simple and ideal quarantine measure
is considered in which an individual is detected with a probability immediately
after it becomes infected and the detected one and its neighbors are promptly
isolated. The efficiency of this quarantine in suppressing a
susceptible-infected-removed (SIR) model is tested in random graphs and
uncorrelated scale-free networks. Monte Carlo simulations are used to show that
the prompt quarantine measure outperforms random and acquaintance preventive
vaccination schemes in terms of reducing the number of infected individuals.
The epidemic threshold for the SIR model is analytically derived under the
quarantine measure, and the theoretical findings indicate that prompt
executions of quarantines are highly effective in containing epidemics. Even if
infected individuals are detected with a very low probability, the SIR model
under a prompt quarantine measure has finite epidemic thresholds in fat-tailed
scale-free networks in which an infected individual can always cause an
outbreak of a finite relative size without any measure. The numerical
simulations also demonstrate that the present quarantine measure is effective
in suppressing epidemics in real networks.Comment: 10 pages, 7 figure
Sudden spreading of infections in an epidemic model with a finite seed fraction
We study a simple case of the susceptible-weakened-infected-removed model in
regular random graphs in a situation where an epidemic starts from a finite
fraction of initially infected nodes (seeds). Previous studies have shown that,
assuming a single seed, this model exhibits a kind of discontinuous transition
at a certain value of infection rate. Performing Monte Carlo simulations and
evaluating approximate master equations, we find that the present model has two
critical infection rates for the case with a finite seed fraction. At the first
critical rate the system shows a percolation transition of clusters composed of
removed nodes, and at the second critical rate, which is larger than the first
one, a giant cluster suddenly grows and the order parameter jumps even though
it has been already rising. Numerical evaluation of the master equations shows
that such sudden epidemic spreading does occur if the degree of the underlying
network is large and the seed fraction is small.Comment: 9 page
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